Top Machine Learning Jobs in Toronto

Design, build, and deploy scalable ML solutions using GCP and Vertex AI. Collaborate with teams to operationalize models and monitor performance.

The Senior Data Scientist will develop machine learning models and data-driven solutions, mentor junior scientists, and drive strategy within the Advanced Data & Analytics team.

The role involves architecting deep neural networks for object detection and tracking, optimizing performance, and developing data strategies in a low-data environment.

As a Senior Machine Learning Engineer, you'll manage the ML lifecycle, develop ML models, collaborate with teams, and optimize systems for production deployment.

As a Senior Machine Learning Developer, you'll design, develop, and maintain machine learning models, collaborate with teams, and present technical solutions to non-technical members while working with large datasets.

The role involves using machine learning and big data technologies to derive insights, design predictive models, and develop data-driven solutions while collaborating with stakeholders to enhance decision making and business strategies.

The Principal Machine Learning Architect will design and implement data-centric ML solutions, ensuring high-quality ML model development and deployment strategies for a leading ad tech company.

Seeking Machine Learning Systems Engineers to build end-to-end 3D native ML systems, focusing on training and inference challenges.

Responsible for designing experiments to evaluate AI models, developing evaluation methodologies, analyzing performance data, and collaborating on production insights.

Design and develop scalable, high-performance data and API infrastructure for real-time processing. Mentor engineers and collaborate with teams to enhance AI model evaluations.

The Machine Learning Scientist will lead open-source research, design experiments, develop novel methodologies, and analyze large-scale data to advance AI model evaluation and transparency.

As a Customer Engineer, you'll bridge technical problems and client needs in analytics and ML, designing data solutions and ensuring high-quality feature delivery.

The Associate Product Manager will work with analytics, ML, and product teams to develop features based on data insights, ensuring effective data management and customer outcomes.

As an AI/ML Architect, you will define architecture for AI solutions, guide teams, mentor, and align initiatives with business goals, focusing on ethical practices.

The role involves developing high-performance AI features for observability, rapid prototyping, and cross-functional collaboration, aimed at improving incident response and system behavior understanding.

The Senior ML/RL Engineer will develop behavior models, implement RL algorithms focusing on safety, design reward functions and optimize training environments while collaborating across teams.

As a Principal AI/ML Architect, you will lead ML assessments, provide architectural guidance, and advise on ML operations across diverse client engagements, ensuring technical quality and building customer confidence through high-quality proof of concepts.

As a Senior Machine Learning Engineer, you will develop and deploy ML models for health data analysis, collaborating with cross-functional teams to ensure reliability and regulatory compliance.

The Machine Learning Engineer will develop and deploy ML models, leveraging analytical skills to automate processes and reveal data value.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

The role involves end-to-end machine learning lifecycle management, including data processing, model development, rigorous testing, and production deployment, focusing on large quantitative models for AI-first products.

The Machine Learning Engineer will manage the ML lifecycle, develop models, ensure performance, and collaborate with a diverse team to build AI-first products.

The AI/ML Engineer will develop and optimize machine learning models, focusing on conversational systems, multi-agent solutions, and scalability, while collaborating across teams to enhance user experiences.

Collaborate with engineers to build AI design systems, optimize data infrastructure, and manage large-scale distributed systems for model development.

Responsible for software integration and quality for Cerebras AI platform, focusing on automation, debugging, and cross-team collaboration. Develops QA strategies and testing methodologies to ensure product quality.